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Fusion-in-Decoder (FiD) is a model described in the following paper:
Izacard, Gautier, and Édouard Grave. Leveraging Passage Retrieval with Generative Models for Open Domain Question Answering. Proceedings of the 16th Conference of the European Chapter of the Association for Computational Linguistics: Main Volume. 2021.
We have replicated FiD training with our Wikipedia corpus variants and incorporated the model into our PyGaggle neural text ranking library.
Our own efforts are described in the paper entitled:
Pre-Processing Matters! Improved Wikipedia Corpora for Open-Domain Question Answering.
This is a FiD-large reader model for the wiki-text-6-3 corpus variant trained on the TriviaQA dataset.
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